Facial airflow enhances the benefits of exercise training in people with chronic lung disease: a randomised controlled trial
Bibliographic record
Abstract
Introduction Breathlessness limits exercise training intensity in people with chronic lung disease (CLD). Stimulation of the trigeminal nerve via fan-to-face (F2F) therapy (facial airflow) can reduce exertional breathlessness and improve exercise endurance in CLD. This randomised controlled trial tested the hypothesis that adding F2F therapy to an exercise training programme could enhance the benefits of exercise training on exercise endurance time (EET) and exertional breathlessness in adults with CLD by allowing them to train at higher intensities. Methods 23 participants with COPD (n=19) or interstitial lung disease (n=4) were randomised to 5 weeks of thrice weekly supervised exercise training with (F2F; n=12) or without (no fan (NF); n=11) facial airflow. Primary outcomes were baseline to post-exercise training change in EET and isotime breathlessness intensity ratings assessed using constant work-rate cardiopulmonary treadmill exercise testing. Results Cumulative exercise training volume over the 5-week exercise training programme was similar in the F2F and NF groups, whereas breathlessness intensity ratings were consistently lower across all exercise training sessions in the F2F group. Both the F2F and NF groups showed significant increases in EET (mean± sd 7.2±9.1 min, 95% CI 3.0–13.6 min, versus 8.6±8.5 min, 95% CI 6.3–9.0 min, respectively) and decreases in isotime breathlessness intensity ratings (−2.1±1.5 min, 95% CI 0.6–3.2 min, versus −1.5±1.1 min, 95% CI 0.8–4.0 min, respectively) from baseline to post-exercise training, with similar magnitudes of change observed between groups. Conclusion F2F therapy (facial airflow) is a simple, feasible, low-cost, low-resource nonpharmacological approach to reduce exertional breathlessness during an exercise training programme in people with CLD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".